{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/deft-a-corpus-for-definition-extraction-in","title":"DEFT: A corpus for definition extraction in free- and semi-structured text","arxiv_id":null,"date":"2019-08-01","proceeding":"WS 2019 8","authors":["Sasha Spala","Nicholas A. Miller","Yiming Yang","Franck Dernoncourt","Carl Dockhorn"],"abstract":"Definition extraction has been a popular topic in NLP research for well more than a decade, but has been historically limited to well-defined, structured, and narrow conditions. In reality, natural language is messy, and messy data requires both complex solutions and data that reflects that reality. In this paper, we present a robust English corpus and annotation schema that allows us to explore the less straightforward examples of term-definition structures in free and semi-structured text.","url_abs":"https://aclanthology.org/W19-4015","url_pdf":"https://aclanthology.org/W19-4015.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[],"tasks":[{"task_slug":"definition-extraction","task_name":"Definition Extraction"}],"methods":[],"datasets_introduced":[{"slug":"deft-corpus","name":"DEFT Corpus","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}